modelsight 0.2.0

Better insights into Machine Learning models performance

Modelsight

Better insights into Machine Learning models performance.

Modelsight is a collection of functions that create publication-ready graphics for the visual evaluation of binary classifiers adhering to the scikit-learn interface.

Modelsight is strongly oriented towards the evaluation of already fitted ExplainableBoostingClassifier of the interpretml package.

Installation

$ pip install modelsight

Usage

See the example notebook.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

modelsight was created by Francesco Pisu. It is licensed under the terms of the GNU General Public License v3.0 license.

Roadmap

Features:

• Average Receiver-operating characteristic curves
• Average Precision-recall curves
• Feature importance (Global explanation)
• Individualized explanations (Local explanation)

CI/CD:

• Integration with GH Actions

Credits

modelsight was created with cookiecutter and the py-pkgs-cookiecutter template.